Evidence map›Paper›PMID 34858165›Full record

ArticleFrontiers in pharmacology2021

Identifying the Effect of Ursolic Acid Against Triple-Negative Breast Cancer: Coupling Network Pharmacology With Experiments Verification.

Yubao Zhang, Xiaoran Ma, Huayao Li, Jing Zhuang, Fubin Feng, Lijuan Liu, Cun Liu, Changgang Sun

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 18 citations in OpenAlex.

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  6. Exploring the therapeutic potential andFrontiers in pharmacology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Yubao ZhangSchool of Basic Medicine, Qingdao University, Qingdao, China.
Xiaoran MaFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China.
Huayao LiCollege of Basic Medical, Shandong University of Traditional Chinese Medicine, Jinan, China.
Jing ZhuangDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, China.
Fubin FengDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, China.
Lijuan LiuDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, China.
Cun LiuFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China.
Changgang SunDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, China.
Weifang Chinese Medicine Hospital · CNShandong University of Traditional Chinese Medicine · CNQingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple negative breast cancer (TNBC) is a subtype of breast cancer with complex heterogeneity, high invasiveness, and long-term poor prognosis. With the development of molecular pathology and molecular genetics, the gene map of TNBC with distinctive biological characteristics has been outlined more clearly. Natural plant extracts such as paclitaxel, vinblastine, colchicine etc., have occupied an important position in the treatment of hormone-independent breast cancer. Ursolic acid (UA), a triterpenoid acid compound derived from apple, pear, loquat leaves, etc., has been reported to be effective in a variety of cancer treatments, but there are few reports on the treatment of TNBC. This study performed comprehensive bioinformatics analysis and

Indexed as

antiproliferativemolecular dockingnetwork pharmacologytriple-negative breast cancerursolic acid

Identifiers

PMID34858165
PMCPMC8631906
OpenAlexW3214356749

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.